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Lattice constant

The lattice constant, often referred to more generally as lattice parameters in , defines the fundamental dimensions of the repeating in a , consisting of the edge lengths a, b, and c along the principal axes, as well as the interaxial angles α (between b and c), β (between a and c), and γ (between a and b). In highly symmetric systems like cubic crystals, where a = b = c and all angles are 90°, a single a—the along the edge—sufficiently characterizes the periodicity, as exemplified by silicon's value of 5.43 Å (at 25 °C) in its face-centered cubic structure. These parameters encapsulate the geometric arrangement of atoms in the , enabling the description of the entire infinite crystal as a translationally periodic array of identical points.

Definition and Basics

Definition

The lattice constant refers to the geometric parameters that define the unit cell of a crystal lattice, specifically the lengths of its edges—denoted as a, b, and c—and the interaxial angles between them, denoted as \alpha, \beta, and \gamma. These parameters precisely describe the size and shape of the unit cell, which serves as the fundamental building block of the crystal structure. The unit cell is the smallest in a that, when repeated by in three dimensions, reproduces the entire periodic arrangement of atoms or molecules. constants encapsulate the inherent periodicity of this arrangement, providing a quantitative measure of the repeating distances and orientations within the . By specifying the edge lengths and angles, lattice constants establish the overall dimensions and symmetry of the crystal, which can range from highly symmetric forms like to lower-symmetry triclinic ones. This foundational role allows crystallographers to classify materials into one of the seven based on these parameters. The concept of lattice constants emerged in early 20th-century crystallography, building on the pioneering work of William Henry Bragg and his son William Lawrence Bragg, who in 1912–1913 derived Bragg's law for X-ray diffraction, enabling the first quantitative determinations of atomic spacings and lattice dimensions in crystals.

Crystal Systems and Parameters

Crystals are classified into seven crystal systems based on the symmetry of their lattice, which determines the relationships among the lattice parameters: the lengths of the unit cell edges (a, b, c) and the angles between them (α between b and c, β between a and c, γ between a and b). These systems range from the lowest symmetry in triclinic to the highest in cubic, with each system accommodating specific Bravais lattices—14 unique lattice types in total that describe the possible arrangements of lattice points. The triclinic system has no symmetry-imposed restrictions, requiring all six parameters to be unequal: a ≠ b ≠ c, α ≠ β ≠ γ ≠ 90°. It includes only the primitive (simple) Bravais lattice. An example is microcline feldspar. In the monoclinic system, symmetry constrains α = γ = 90° while β ≠ 90°, and a ≠ b ≠ c. It features two Bravais lattices: primitive and base-centered. Gypsum (CaSO₄·2H₂O) exemplifies this system. The orthorhombic system imposes orthogonal axes with α = β = γ = 90° and a ≠ b ≠ c. It supports four Bravais lattices: primitive, base-centered, body-centered, and face-centered. Topaz and olivine are representative materials. Tetragonal symmetry equates two axes with a = b ≠ c and α = β = γ = 90°. Two Bravais lattices exist: primitive and body-centered. β-Tin (white tin) is a common example. The trigonal (or rhombohedral) system features a = b = c and α = β = γ ≠ 90°. It has a single primitive Bravais lattice, often described using a hexagonal setting for convenience. Calcite (CaCO₃) illustrates this system. Hexagonal symmetry sets a = b ≠ c, α = β = 90°, and γ = 120°, with one primitive Bravais lattice. Materials like and magnesium adopt this structure. The cubic system exhibits the highest , with a = b = c and α = β = γ = 90°. It includes three Bravais lattices: , body-centered, and face-centered. Examples include (NaCl) and . Within these systems, lattice parameters can describe either unit , which contain exactly one lattice point and represent the smallest repeating volume, or conventional unit , which may contain multiple lattice points for higher but are chosen for their orthogonal or symmetric geometry. For instance, in the face-centered cubic , the conventional cell has four lattice points, while a primitive cell would have one but with non-orthogonal vectors.
Crystal SystemLattice ParametersBravais LatticesExample Material
Triclinica ≠ b ≠ c; α ≠ β ≠ γPrimitive
Monoclinica ≠ b ≠ c; α = γ = 90°, β ≠ 90°Primitive, Base-centered
Orthorhombica ≠ b ≠ c; α = β = γ = 90°Primitive, Base-centered, Body-centered, Face-centered
Tetragonala = b ≠ c; α = β = γ = 90°Primitive, Body-centeredβ-Tin
Trigonala = b = c; α = β = γ ≠ 90°Primitive
Hexagonala = b ≠ c; α = β = 90°, γ = 120°Primitive
Cubica = b = c; α = β = γ = 90°Primitive, Body-centered, Face-centeredNaCl

Properties and Dependencies

Unit Cell Volume

The volume of the unit cell, denoted as V, is a fundamental property derived directly from the and , serving as the basis for calculating material density and atomic packing efficiency. For the most general case of a , the unit cell volume is given by the formula V = abc \sqrt{1 - \cos^2 \alpha - \cos^2 \beta - \cos^2 \gamma + 2 \cos \alpha \cos \beta \cos \gamma}, where a, b, and c are the , and \alpha, \beta, and \gamma are the interaxial . This expression arises from the scalar triple product of the lattice vectors, representing the parallelepiped volume. In higher-symmetry systems, the formula simplifies due to constraints on the parameters; for instance, in the cubic system where a = b = c and \alpha = \beta = \gamma = 90^\circ, V = a^3; in the tetragonal system where a = b, \alpha = \beta = \gamma = 90^\circ, V = a^2 c; and in the hexagonal system where a = b, \alpha = \beta = 90^\circ, \gamma = 120^\circ, V = a^2 c \sin 60^\circ = a^2 c \sqrt{3}/2. The unit cell volume is essential for determining the theoretical \rho of a crystalline material, which quantifies the mass per unit and reflects packing efficiency. The is calculated as \rho = \frac{Z M}{N_A V}, where Z is the number of atoms (or units) per , M is the , and N_A is Avogadro's number. This relation allows direct computation of \rho once parameters are known, providing insight into material properties like mechanical strength and without requiring bulk measurements. For example, in , which adopts a cubic structure with lattice constant a \approx 3.567 , the volume is V = a^3 \approx 45.4 ³. This value, combined with Z = 8 carbon atoms per and M = 12.01 g/mol, yields a theoretical of approximately 3.51 g/cm³, consistent with experimental observations.

Temperature, Pressure, and Other Dependencies

The of a typically increases with due to , a quantified by the linear thermal expansion coefficient \alpha_L = \frac{1}{a} \frac{da}{dT}, where a is the lattice parameter. For small temperature changes, this leads to the approximate relation a(T) = a_0 (1 + \alpha_L \Delta T), with a_0 as the reference lattice constant at temperature T_0. In semiconductors like , \alpha_L is positive and relatively small at , on the order of $2.618 \times 10^{-6} K^{-1} at 300 K, reflecting the material's low thermal expansion compared to metals. This expansion arises from anharmonic vibrations in the , where interactions cause atoms to occupy larger average positions as rises, influencing properties such as bandgap energy and thermal conductivity. Under applied , the lattice constant decreases due to , governed by the material's \beta = -\frac{1}{V} \frac{dV}{dP}, where V is the unit cell volume and P is ; the K = 1/\beta measures resistance to uniform . For instance, exhibits exceptional incompressibility with K \approx 442 GPa at ambient conditions, allowing only minimal lattice contraction even at gigapascal , which underscores its use in high- environments. The pressure dependence often follows a for small changes, but higher pressures reveal nonlinear behavior captured by equations of state like the Birch-Murnaghan form, where lattice parameters shrink anisotropically in non-cubic crystals. This alters interatomic distances, affecting and . Other factors can induce subtle changes in the lattice constant. In piezoelectric materials, an applied causes lattice strain via the converse piezoelectric effect, leading to deformations on the order of picometers per volt; for example, in (PZT) thin films, the c-axis lattice parameter shifts measurably under fields up to several kV/cm, enabling applications in actuators. Magnetostrictive effects in ferromagnetic materials similarly alter lattice dimensions in response to magnetic fields, with strains typically below 0.1%; in Nd_2Fe_{14}B permanent magnets, influences secondary phase lattice constants, causing expansions or contractions aligned with magnetization direction. Isotopic composition also plays a role, as lighter isotopes result in slightly larger lattice constants due to reduced zero-point motion in quantum vibrations; in , the lattice parameter decreases by about $5.4 \times 10^{-4} Å from nearly pure ^{12}C to ^{13}C-enriched samples at . Phase transitions can cause abrupt changes in constants, particularly in martensitic transformations, which are diffusionless and shear-dominated. In steels, the face-centered cubic to body-centered tetragonal transition upon rapid cooling results in a volume expansion of approximately 4%, driven by the denser packing of and trapped carbon, leading to internal stresses and enhanced . This discontinuous shift in lattice parameters exemplifies how structural instabilities under temperature or stress can profoundly impact material properties without atomic diffusion.

Determination Methods

Experimental Techniques

Experimental techniques for determining lattice constants primarily involve diffraction-based methods, which probe the periodic arrangement of atoms through wave , and direct imaging techniques that visualize atomic-scale periodicity. These approaches provide empirical measurements essential for characterizing crystal structures in materials such as metals, semiconductors, and ceramics. Diffraction methods leverage the patterns produced by waves interacting with planes, while imaging techniques offer real-space resolution at the nanoscale. X-ray diffraction (XRD) remains the cornerstone for lattice constant measurement due to its high precision and applicability to a wide range of materials. The technique operates on Bragg's law, expressed as
n\lambda = 2d \sin\theta,
where n is a positive integer denoting the order of diffraction, \lambda is the X-ray wavelength, d is the spacing between crystal planes (directly related to lattice parameters), and \theta is the incident angle of the X-ray beam. In powder XRD, a finely ground polycrystalline sample is irradiated, producing a concentric ring pattern or linear peaks that correspond to multiple lattice orientations; these data are refined using methods like the Rietveld approach to extract lattice parameters with sub-angstrom accuracy. Single-crystal XRD, by contrast, involves rotating a well-faceted crystal in the beam to capture specific reflections, enabling detailed indexing of the unit cell and refinement of parameters like a, b, and c in orthorhombic systems. This method is particularly effective for bulk materials but requires high-quality crystals free of defects to minimize peak broadening.
Neutron diffraction serves as a complementary technique, especially for materials containing light elements like or , where X-rays interact weakly, or for probing magnetic structures that influence parameters. It follows principles analogous to but uses a beam of thermal s with wavelengths typically around 1 , generated from nuclear reactors or spallation sources. The interplanar spacing d is again derived from angles via a modified , with advantages in penetrating deeper into samples (up to centimeters) compared to X-rays. Powder neutron is common for isotopic studies, such as determining expansion in hydrides, while single-crystal setups allow for anisotropic measurements; however, access to facilities limits its routine use. Electron diffraction techniques, including selected area electron diffraction (SAED) in transmission electron microscopy (TEM) and low-energy electron diffraction (LEED), are vital for analyzing thin films, nanostructures, and surface lattices where bulk methods fall short. In TEM-based SAED, a focused electron beam (wavelength ~0.0025 nm at 200 kV) passes through a thin sample region, producing spot patterns that map reciprocal lattice vectors; the in-plane lattice constant is calculated from ring diameters or spot separations, offering resolutions down to 0.01 Å for epitaxial layers. LEED, employed in ultra-high vacuum for surfaces, directs low-energy electrons (20-200 eV) at a single-crystal face, yielding diffraction spots whose spacing inversely relates to the surface lattice periodicity; it excels in monitoring reconstructions or adsorbate-induced changes in real time. These methods provide localized information but are sensitive to sample thickness and contamination. Direct imaging via (AFM) and (STM) enables visualization of lattice periodicity without relying on , ideal for conductive or insulating surfaces at ambient or vacuum conditions. STM measures tunneling current between a sharp tip and sample atoms, resolving atomic lattices with sub-angstrom precision; for instance, the hexagonal lattice constant of can be directly quantified from topographic protrusions spaced ~0.246 apart. AFM, using tip-sample force interactions in contact or tapping modes, images insulating materials like oxides, where Fourier transforms of height maps extract lattice parameters from periodic features. Both techniques demand atomically flat surfaces and ultra-stable setups to avoid artifacts from tip convolution. Achieving high accuracy in these measurements hinges on instrumental resolution, sample quality, and data analysis. typically resolves lattice constants to ~0.001 , limited by angular precision (±0.001°) and wavelength calibration, though errors can arise from if not controlled. diffraction offers similar precision but with larger uncertainties (~0.005 ) due to beam flux variability. methods reach ~0.01 but suffer from relativistic effects in TEM and surface sensitivity in . Sample preparation is critical: powders must be randomly oriented and free of preferred textures, thin films require uniform thickness (<100 nm for TEM), and surfaces for AFM/ need cleaning to expose clean lattices. Environmental factors like temperature stabilization (to ±0.1 ) and levels further enhance reliability, ensuring measurements reflect intrinsic lattice parameters rather than extrinsic distortions.

Theoretical Calculations

Theoretical calculations of constants rely on computational models that simulate atomic interactions to determine the of structures, typically by minimizing the total energy with respect to lattice parameters. These approaches range from first-principles quantum mechanical methods, which require no empirical input beyond fundamental constants, to semi-empirical potentials fitted to experimental data. Such predictions are essential for understanding material properties before synthesis and for systems where experiments are challenging. Density functional theory (DFT), grounded in the Hohenberg-Kohn theorems and implemented via the Kohn-Sham equations, is the most widely used method for calculating lattice constants in solids. The equilibrium lattice parameter is obtained by optimizing the unit cell volume that minimizes the total energy, often incorporating exchange-correlation functionals like the local density approximation (LDA) or generalized gradient approximation (GGA). Software such as the (VASP), which employs plane-wave basis sets and pseudopotentials, or , an open-source suite for electronic-structure calculations, facilitates these computations for complex crystals. For semiconductors, DFT yields lattice constants with typical errors of ±1-2% relative to experimental values, with LDA slightly underestimating and GGA slightly overestimating due to approximations in electron correlation. For instance, LDA-DFT calculations for predict a lattice constant of approximately 5.38 , underestimating the experimental value of 5.431 by about 1%. Other techniques, such as Hartree-Fock () methods, solve the many-electron approximately by neglecting electron correlation, leading to predictions of lattice constants that are generally less accurate than DFT, often overestimating by several percent. approaches, implemented in codes like , provide a basis for post- corrections like Møller-Plesset but are computationally intensive for large systems. Empirical potentials offer computationally efficient alternatives for preliminary estimates or large-scale simulations. The , a pairwise model balancing repulsive and attractive van der Waals forces, is applied to simple cubic or close-packed s of rare gases or molecular crystals, where the equilibrium lattice spacing emerges from the potential minimum. For metallic systems, the embedded-atom (EAM), introduced by Daw and Baskes, incorporates many-body energies to better capture delocalized electrons, with parameters fitted to reproduce observed lattice constants, elastic moduli, and defect energies in face-centered cubic or body-centered cubic metals.

Applications

Lattice Matching

Lattice matching in epitaxial growth involves aligning the lattice constants of the and the overlying to minimize interfacial strain and promote coherent, defect-free heterostructures. The lattice mismatch f, defined as f = \frac{a_\mathrm{substrate} - a_\mathrm{film}}{a_\mathrm{substrate}}, quantifies the relative difference in lattice parameters, where positive values indicate compressive strain in the film and negative values indicate tensile strain. Small mismatches (|f| < 0.1\%) allow for pseudomorphic growth, in which the film lattice conforms to that of the without introducing dislocations. The maximum thickness for maintaining this coherent epitaxy is the critical thickness h_c, beyond which misfit dislocations nucleate to partially relax the strain. According to the Matthews-Blakeslee model, this thickness is approximated by h_c \approx \frac{b}{f} \frac{1 - f^2}{8\pi (1 + \nu) \sqrt{1 - \nu/4}}, where b is the magnitude of the of the and \nu is the of the film material; this equilibrium model balances the misfit stress driving dislocation motion against the line tension opposing it. Exceeding h_c results in strain relaxation via dislocation glide, but for thicknesses below this limit, the pseudomorphic interface preserves high structural quality essential for device functionality. In semiconductor heterostructures, lattice matching is vital for applications requiring low defect densities, such as optoelectronics. A prominent example is the growth of Al_xGa_{1-x}As on GaAs substrates, where the lattice constant of GaAs is 5.653 Å at room temperature, and the aluminum fraction x is tuned to achieve near-zero mismatch (typically |f| \approx 0.01\%). This enables the fabrication of high-performance light-emitting diodes (LEDs) and laser diodes, where the abrupt interfaces confine carriers and enhance radiative recombination efficiency. Significant mismatch leads to incomplete relaxation through misfit dislocations at the , which can multiply and generate threading dislocations that extend into the active layers. These threading dislocations, with densities often exceeding $10^8 cm^{-2} for mismatches above 2%, introduce non-radiative recombination centers and electrical leakage paths, severely degrading device performance and reliability. To mitigate defects in cases of moderate mismatch, buffer layers are interposed between the substrate and film to facilitate gradual lattice adjustment, distributing strain and blocking dislocation propagation from the interface. These buffers, often compositionally graded or composed of intermediate materials, enable the growth of high-quality films on otherwise incompatible substrates while maintaining low threading dislocation densities below $10^6 cm^{-2}.

Lattice Grading

Lattice grading refers to the technique of gradually varying the composition of an layer to achieve a smooth transition in its constant, thereby accommodating lattice mismatch between and overlying films. In alloys such as Al_xGa_{1-x}As, the aluminum x is systematically increased or decreased during epitaxial growth, resulting in a parameter that interpolates linearly between 5.6533 Å for GaAs (x=0) and 5.6612 Å for AlAs (x=1), in accordance with . This compositional variation spreads the lattice mismatch over the thickness of the graded layer, preventing abrupt interfaces that could lead to high localized strain. The primary benefits of lattice grading include a significant reduction in total by distributing the mismatch gradually, which suppresses the formation of misfit dislocations and allows for the deposition of thicker coherent films beyond the Matthews-Blakeslee critical thickness. This enables the integration of materials with substantial lattice differences in heterostructures while maintaining structural integrity. However, the process requires slower growth rates and extended deposition times to precisely control the composition gradient, introducing a in fabrication . A representative application is in multi-junction solar cells, where compositionally graded InGaP buffers on GaAs substrates facilitate the growth of lattice-mismatched InGaAs subcells by providing a controlled strain relaxation pathway. Such grading can produce bow-shaped strain profiles across the layer, contributing to that must be managed during processing. To optimize these profiles, finite element analysis is employed to simulate the mechanical strain distribution and predict the evolution of lattice parameters under varying composition gradients, ensuring minimal residual stress and defect densities in the final structure.

Strain Engineering and Defects

In epitaxial growth, lattice constant mismatches between substrate and film materials induce strain, which can be classified as biaxial or uniaxial depending on the growth orientation and constraints. Biaxial strain occurs predominantly in pseudomorphic growth on (001)-oriented substrates, where the film is compressed or expanded equally in the plane parallel to the interface, leading to a perpendicular expansion or contraction via the Poisson effect. Uniaxial strain, in contrast, applies along a single in-plane direction, often engineered using compliant substrates to achieve directional control for specific electronic properties. Initially elastic, this strain remains coherent below a critical thickness determined by the balance between strain energy and dislocation energy; beyond this, plastic deformation occurs, introducing defects to relieve the mismatch. Lattice mismatches exceeding about 2-7% typically drive the formation of defects such as misfit dislocations and stacking faults during heteroepitaxial . Misfit dislocations form at the to accommodate , with their governed by the equilibrium between continued accumulation and the energy cost of dislocation introduction, as described in the Matthews-Blakeslee model. Stacking faults arise as planar defects disrupting the atomic stacking sequence, often nucleating from partial dislocations or during relaxation in materials like III-nitrides, where they propagate as low-energy pathways for strain relief. The prevalence of these defects is influenced by modes; in the Frank-van der Merwe layer-by-layer mode, favored for small mismatches (<2%), coherent minimizes defects initially, but larger mismatches promote island nucleation (Volmer-Weber mode) or mixed Stranski-Krastanov modes, exacerbating dislocation formation through energy minimization at the . Strain engineering mitigates these defects while harnessing strain for property tuning, particularly through superlattices and quantum wells. Strain-compensated superlattices alternate compressively and tensilely strained layers, such as InGaAs/GaAs and GaAsP/GaAs, to balance net strain and suppress misfit dislocations, enabling thicker coherent structures for mid-infrared lasers. In quantum wells, controlled biaxial compressive strain in InGaAs layers on GaAs substrates shifts the band gap via deformation potentials and induces piezoelectric fields due to shear strain components, altering carrier confinement and enabling wavelength tuning in optoelectronic devices. These piezoelectric effects generate internal electric fields up to 100 kV/cm in non-centrosymmetric strained layers, screening quantum-confined Stark shifts for enhanced modulator performance. In modern two-dimensional materials, substrate-induced breaking of sublattice symmetry in epitaxial on SiC substrates (with contributions from biaxial tensile strain of ~0.5% due to differences) induces a band gap of approximately 0.26 eV in films, which diminishes in multilayers. This approach facilitates bandgap engineering for applications without destructive gating.

Common Values

Elemental Materials

The lattice constants of pure elemental crystals are fundamental parameters that define the periodic arrangement of atoms in their stable structures at 25°C and . These values are typically determined through and are compiled in authoritative references, with ongoing refinements from high-precision measurements to account for isotopic effects and thermal expansions. The table below organizes representative examples by , focusing on common metals, semiconductors, and select rare earth elements; all values are experimental unless noted otherwise.
Crystal SystemElementStructure TypeLattice Parameters (Å)Notes
Cubic (Diamond)a = 3.5668Stable allotrope at 25°C; value from high-resolution measurements.
Cubic (Diamond)a = 5.431020511CODATA recommended value at 25°C, refined from interferometric measurements post-2018.
Cubic (Diamond)a = 5.6575At 25°C; similar to Si but larger due to atomic size.
Cubic (FCC)AluminumFace-centered cubica = 4.0496At 25°C; ductile metal structure.
Cubic (FCC)Face-centered cubica = 3.6149At 25°C; common in electrical applications.
Cubic (FCC)Face-centered cubica = 4.0786At 25°C; .
Cubic (FCC)LeadFace-centered cubica = 4.9505At 25°C; soft metal.
Cubic (BCC)Ironα (body-centered cubic)a = 2.8664At 25°C; ferromagnetic stable below 912°C.
Cubic (BCC)Body-centered cubica = 4.2906At 25°C; .
Hexagonal (HCP)MagnesiumHexagonal close-packeda = 3.2095, c = 5.2111At 25°C; lightweight metal.
Hexagonal (HCP) (α)Hexagonal close-packeda = 2.9504, c = 4.6863At 25°C; stable low-temperature allotrope.
Hexagonal (HCP)Hexagonal close-packeda = 2.6650, c = 4.9470At 25°C; exhibits c/a deviation from .
Hexagonal (HCP) (α)Hexagonal close-packeda = 3.6336, c = 5.7810At 25°C; rare earth metal.
Cubic (BCC) (β)Body-centered cubica = 3.306Extrapolated to ; high-temperature allotrope stable above 882°C, with recent DFT-validated measurements confirming value.
Certain elements display polymorphism, where different allotropes adopt distinct systems and parameters; for instance, titanium's α-phase is hexagonal close-packed at ambient conditions, transitioning to the body-centered cubic β-phase at elevated temperatures, which affects its mechanical properties in applications. Similarly, iron's α-BCC form at converts to FCC γ-phase above 912°C. These values are standard references at 25°C, with post-2020 refinements primarily enhancing precision for semiconductors like through advanced , reducing uncertainty to parts per billion.

Compound Semiconductors and Alloys

Compound semiconductors, particularly those in the III-V family, adopt the and possess that enable their widespread use in optoelectronic devices such as lasers and solar cells. These materials often feature around 5-6 , facilitating epitaxial growth when matched appropriately. Binary compounds like (GaAs) have a of 5.653 , while indium phosphide (InP) exhibits 5.869 , both measured at . Silicon carbide (SiC), a wide-bandgap IV-IV compound, exists in various hexagonal polytypes, with the technologically important 4H-SiC polytype displaying lattice constants of a = 3.073 and c = 10.053 . oxides, such as (BaTiO₃), adopt a tetragonal at with a = 3.994 and c = 4.033 , influencing their ferroelectric properties.
MaterialCrystal StructureLattice Constant (Å)
GaAsZincblendea = 5.653
InPZincblendea = 5.869
4H-SiCHexagonala = 3.073, c = 10.053
BaTiO₃Tetragonala = 3.994, c = 4.033
In alloys such as AlₓGa₁₋ₓAs, the lattice constant varies approximately linearly with composition according to , yielding a(x) ≈ 5.653 + 0.0075x , where x is the aluminum ; this approximation holds well for low to moderate x but shows slight deviations at higher compositions due to bonding effects. Emerging materials include two-dimensional transition metal dichalcogenides like (MoS₂), which has a constant of a = 3.16 in its bulk 2H phase, relevant for and . Hybrid organic-inorganic perovskites, such as methylammonium lead iodide (CH₃NH₃PbI₃), exhibit a cubic structure with a ≈ 6.31 at elevated temperatures, making them promising for photovoltaic applications despite phase transitions affecting stability. Lattice constants in these compound semiconductors and alloys can exhibit variability under external influences, such as strain in epitaxial layers, where mismatches lead to biaxial strains altering parameters by up to 1%, thereby tuning electronic properties without introducing excessive defects.

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